I have a Stata program that obtains a column vector, say r(X) by calling another program. I want to put the
values of r(X) into a variable in the original dataset, which for me is complicated by -marksample-.
The values of r(X) arrive in the same order as the original data would be if cases not selected by
-marksample- were dropped. So, if were there no use of marksample, the row index of r(X) would
correspond to _n, and there would be no difficulty; -svmat- will align the contents of r(X) as desired.
But this is not true because the data are processed -if `touse'-, so that the first element of r(X) might
correspond to the 4th observation of the original data set, the second element to the 7th observation,
and so forth.
My thinking so far involves reconstructing the r(X) matrix into another matrix, putting in missing values
as indicated by -touse-, per my fragment below. Is there a less lunky way to accomplish this?
(My program might be called many times in a simulation context, so time is an issue.)
This must be an utterly commonly task. (And yes, I could do the same in Mata, but it's still more
or less the same thing.)
program whatever
syntax ...[if] ...
marksample touse
....Other program is called with if `touse', which returns r(X)
// Make r(X) into a variable
X = return(X)
mkmat `touse', matrix(tu)
mat `temp' = J(`=_N',1,.) // working matrix for repacking X
local pos = 1
forval i = 1/`=_N' {
if (tu[`i',1] == 1) {
mat `temp'[`i',1] = `D'[`pos',1]
local ++pos
}
}
svmat `temp', name(Xvar)
Thanks,
Mike Lacy
Dept. of Sociology
Colorado State University
Fort Collins CO 80523-1784
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